land tenure data gap: combining eo data into land governance...

2nd International Doctoral Seminar in filed of Geodesy, Geoinformatics and Geospace

1MSc. Cheonjae Lee | PhD Candidate | Institute of Geodesy, Geoinformatics and Landmanagement

© AP - https://www.apnews.com

Land Tenure Data Gap: Combining EO data into land

governance in Korean (re-)unification

Lee, Cheonjae

Technical University of Munich

Faculty of Civil, Geo and Environmental Engineering

Chair of Land Management

Dubrovnik, Croatia 09. May 2018


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Doctoral Research Package (since October 2016)

MSc. Cheonjae Lee | PhD Candidate | Institute of Geodesy, Geoinformatics and Landmanagement

Theoretical

Empirical

Synthetic

Methodological

Book

Where I am

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THESIS

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NO.3

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NO.2

1st

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2nd

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3rd

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4th

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5th

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6th

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Research Outcomes


A Peer-review Paper

• Lee, C. & de Vries, W.T., 2018, A Divided Nation: Rethinking and rescaling land tenure in Korean (re-)unification. Land Use

Policy.75 (2018), 127-136.

A Conference Paper

• Lee, C., Lu, Y., Wang, M., de Vries, W.T. & Chigbu, U.E., 2017, Transforming land governance: “one-country one-system”

versus “one-country two-systems”. International conference on Sustainable Urban and Regional Development – Research

and Policy Challenges for the Asia-Pacific Rim, Renmin University of China in collaboration with The Regional Science

Academy and Regional Science Association International, Beijing, China, 9-10 December, 2017.

A Workshop Presentation

• Lee, C., 2017, A Divided Nation: Land tenure, governance and Korean re-unification, National Post-Doc and Doctoral

Seminar in Land Management in Germany, Universität der Bundeswehr München, Munich, Germany, 6-7 July 2017. (Oral

presentation)


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Table of Contents

I. Introduction

II. What we can observe from above

III. What we cannot observe from above

IV. What I want to observe

V. Challenges: land tenure data gap

VI. Questions © ABC - http://www.abc.net.au



Inter-Korean summit was held at the ‘Peace

House’ at Panmunjom on April 27, 2018.

• North and South Korea agree to end

Korean war in historic accord.

• Gathering and establishing reliable

information for policy-making in pursuing

(re-)unification is significant.

• But, still in great difficulties in collecting

data due to the concealment from NK.

Introduction

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The availability of earth observation (EO) data

has been increased significantly in many

disciplines.

• Growing interest in measuring the context

of social phenomena and multi-level

analysis using EO data.

• Land use and land cover (LULC) change

information comprises essential

geographical spatial features.

Introduction

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© NASA - https://neo.sci.gsfc.nasa.gov



Governing land tenure is a critical component in

(re-)unification setting.

• Land tenure has a pivotal role in reforming

institutions, facilitating peacebuilding and

integration process and territorial development.

• How to re-shape land governance institutions are

a fundamental question focusing on land tenure

security, transferability, legitimacy and identity.

Introduction



Introduction


However, NK rarely disclose and distribute land

tenure (LT)-related information and statistics.

• The scope of relevant researches on land

policies have been very limited and mostly

dependent on the secondary data.

• Scientific and objective acquisition and

accumulation of geospatial information is still

insufficient to support better and more effective

land policy-making for (re-)unification.


Introduction


Many studies using EO data for NK as ‘inaccessible terrain’ have been proposed.

• Nevertheless, researchers and policy-makers still have faced with difficulties in incorporating LT-

related data with EO data due to:

Levels of accessibility: the limited access to NK data

Methodological levels: complexity of integrating LT attributes with EO data

Analytical levels: Its lower reliability and validity of acquired information


Introduction

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Thus, research Objectives are:

RO 1.Potential availability of EO dataTo review the potential availability of EO data and techniques with high-resolution

imagery in Korean (re-)unification settings

RO 2.Merging LT-related data with EO dataTo examine how existing and more traditional LT-related data can be synthesized and

visualized in conjunction with EO data into land management practices as well as

peace and conflict research



• Satellites: LANDSAT 4, 5

• sensors: MMS (Multispectral Scanner System)

and TM (Thematic Mapper)

• Detections:

- (spatial) coastal features; roads and urban

areas; soil/ vegetation differentiation; land/water

boundaries etc.

- (temporal) deforestation; urban and suburban

development; changes in heat islands

vegetation/land use patterns etc.

What we can observe from above




• Satellites: LANDSAT 7, 8, 9

• sensors: ETM + (Enhanced Thematic Mapper)

• Detections:

- (spatial) large buildings; forest stands; agricultural

plots etc.

- (temporal) changes in human infrastructure;

development patterns; migration patterns;

agricultural variations; urban/rural interchange etc.





• Satellites: SPOT 1,2, 4, and 5

• sensors: Two HRV-IR (High Resolution Visible,

Infrared) push-broom sensors; High Resolution

Geometry (HRG); VEGETATION instrument

• Detections:

- (spatial) agriculture; land use, water resources,

geological applications; engineering applications;

forest monitoring; vegetation cover study etc.

- (temporal) deforestation; (sub)urban land use

changes; residential development etc.



© AIRBIS 2018 - https://www.intelligence-airbusds.com


• Satellites: IKONOS 1, 2

• sensors: MMS (Multispectral) and PAN

(Panchromatic)

• Detections:

- (spatial) roads; vehicles; buildings; infrastructures;

land use; agricultural uses; vegetation etc.


development patterns; agricultural variations;

urban/rural interchange etc.




© NGII 2009


• Satellites: Quickbird

• sensors: MS (Multispectral) and PAN

(Panchromatic)

• Detections:

- (spatial) roads; vehicles; buildings; infrastructures;

land use; agricultural uses; vegetation etc.


development patterns; agricultural variations;

urban/rural interchange etc.





City lights at night illustrate dramatically the relative economic importance of cities and a fairly reliable

indicator of where people live.


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Instrument(s): ISS – Digital Camera

Acquired date: 30 January, 2014

Instrument(s): Suomi NPP - VIIRS

Acquired date: 24 September, 2012

© NASA - https://earthobservatory.nasa.gov © NASA - https://earthobservatory.nasa.gov



The South Korean governments (e.g. MoU; MoE) and research institutions has already established

geospatial information using EO data (e.g. mainly using Landsat TM, MODIS, IRS-1C, Quickbird, SPOT-5,

RAPIDEYE, KOMPSAT-2).



© NGII 2009Instrument(s): KOMPSAT - 2


Socio-economic (SE) data is about humans,

human activities, and the space and/or structures

used to conduct human activities

• Sources of SE data include field surveys,

government statistics, government

administrative records, secondary data etc.

• Specific classes entails demographics,

housing, migration, transportation, economics

etc.

What we cannot observe from above

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Key sources of land tenure-related SE data as following:

• Population census (demographical data-oriented)

• Economic census (industry data-oriented)

• Agricultural census (farm economic data-oriented)

• Labour force statistics (workforce data-oriented)

• Land records (land parcel and ownership data-oriented)

• Transportation and infrastructure inventories (SOC data-oriented)

• Administrative records (regulatory / administrative data-oriented)



© NKNEWS 2017


It is possible to collect SE data sources of North Korea from

different platforms. For example (domestic):

• North Korea Statistics (KOSIS, Korean Statistical Information

Services)

• Information Centre on North Korea (MoU, Ministry of Unification)

• Committee for the Five northern Korean Provinces (MOIS,

Ministry of Interior and Safety)

• Cadastral Achieves (NAK, National Achieves of Korea)

• A wide range of research institutions and internet-based

platforms also provide socio-economic data.


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It is possible to collect SE data sources of North Korea from different

platforms. For example (international):

• DPR Korea 2008 Population Census: National Report (Central

Bureau of Statistics, DPR Korea 2009 funded by UNSD)

• National Accounts Main Aggregates Database, Social Indicators,

Demographic Yearbook, Millennium Indicators (UNSD)

• Department of Economic and Social Affairs (UNPD)

• The World Factbook (CIA)

• Human Development Reports (UNDP)

• UNICEF, World Bank, FAO, UNESCAP etc.


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Relationship among land-cover using EO data and socio-economic variables has been established in regional

science field and major applications include: slum detection; quality of life index; house value estimation;

urban growth; population estimation; and social vulnerability assessment (Patino & Duque, 2013).

What I want to observe


Source: Weeks et al., 2007




Source: Wurm & Taubenböck, 2018

Source: Kevin & Duke, 2012




Source: Xie et al., 2016


Many initiatives are tackling the LT data challenge that

make land and resource rights information more

accurate and accessible (Peterson & Stevens, 2014).

• LandMark Map (Global platforms)

• WRI Rights to Resources Map (WRI)

• Focus on Land in Africa (FOLA)

• Mapping for Rights (Rainforest Foundation)

• Land Portal (ILC)

• OpenTitle (Thomson Reuters)

• Country- and regional-focused mapping platforms

(e.g. RAISG; AMAN; Open Development Cambodia; the

Sarawak Geoportal etc.)


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Source: http://www.landmarkmap.org



Land tenure data requires both physical delineation

and demarcation of social relations (Robinson et

al., 2014).

• EO data with locally derived land tenure and

governance variables are particular concerns.

• Correctly documenting the form of tenure is

challenging, measuring tenure security is even

more difficult.

• Tenure security reflects a perception of risk, for

which data are especially scarce.

Challenges: land tenure data gap

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© meniscus - http://www.meniscus.co.uk/unspoken-gaps-data/



• A lack of theoretical foundations linking EO data and LT-

related SE data for accurate data (re-)interpretation

• A lack of knowledge of how to derive reliable values for

the LT-related SE data

• An issue of LT-related SE data simplification and

trivialization.

• Integrating LT-related data and EO data requires the

fusion not only of data, but also of quite different scientific

traditions

Challenges: land tenure data gap



• How does the LULC change link to the

dynamics of land tenure as the social

institutions (e.g. organizations, rules and

restrictions)?

• How can I derive the reliable variables (or

indicators) of EO and LT-related SE data?

• What EO image processing methods and

EO data can be used in predicting pattern

changes of land management (practices) in

(re-)unification settings, especially NK?

Questions


© LANDTHINK 2012

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THANK YOU

FOR YOUR

ATTENTION!

ANY QUESTIONS?

NO? GREAT! BYE.

MSc. Cheonjae Lee

Dubrovnik, Croatia 09. May 2018

land tenure data gap: combining eo data into land governance...

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